Abstract
Point cloud video provides 6 degrees of freedom (6DoF) viewing
experiences to allow users to freely select the viewing angles of 3D
scenes and is expected to be the next-generation video. This paper
studies the point cloud video streaming and proposes a fuzzy logic-based
point cloud video streaming scheme to solve the inherent technical
issues. In particular, a point cloud video is first partitioned into
smaller tiles, along with a low-quality base layer covering the entire
video. Each tile is encoded into different quality levels, and both the
compressed and uncompressed (i.e., decoded) versions of each tile are
prepared for selection. Then, based on the user’s viewing angle and
predicted future network bandwidth condition, fuzzy logic empowered
quality level selection, with properly defined novel fuzzification,
fuzzy rules, and defuzzification, is conducted to maximize the received
point cloud video quality under the communication resource,
computational resource and quality requirements constraints. Extensive
simulations based on real point cloud video sequences and network traces
are conducted, and the results reveal the superiority of the proposed
scheme over the baseline scheme. To the best of our knowledge, this is
the first work studying point cloud video streaming using fuzzy logic.